0 citations0 references

Scalable Hierarchical Aggregation Protocol (SHArP): A Hardware Architecture for Efficient Data Reduction

2016pp. 1–10

Citations Over TimeTop 10% of 2016 papers

Richard L. Graham, Vladimir Koushnir, Lion Levi, Alex Margolin, Tamir Ronen, Alexander Shpiner, Oded Wertheim, Eitan Zahavi, Devendar Bureddy, Pak Lui, Hal Rosenstock, Gilad Shainer, Gil Bloch, Dror Goldenerg, Mike Dubman, Sasha Kotchubievsky

Abstract

Increased system size and a greater reliance on utilizing system parallelism to achieve computational needs, requires innovative system architectures to meet the simulation challenges. As a step towards a new network class of co-processors - intelligent network devices, which manipulate data traversing the data-center network, this paper describes the SHArP technology designed to offload collective operation processing to the network. This is implemented in Mellanox's SwitchIB-2 ASIC, using innetwork trees to reduce data from a group of sources, and to distribute the result. Multiple parallel jobs with several partially overlapping groups are supported each with several reduction operations in-flight. Large performance enhancements are obtained, with an improvement of a factor of 2.1 for an eight byte MPI_Allreduce() operation on 128 hosts, going from 6.01 to 2.83 microseconds. Pipelining is used for an improvement of a factor of 3.24 in the latency of a 4096 byte MPI_Allreduce() operations, declining from 46.93 to 14.48 microseconds.

Related Papers

Application of Non-oriented Traverse and Its Accuracy Analysis(2002)
Surface Precise Traverse Survey for Metro Works(2008)
The Method about Application of Excel to Adjust Singleness Traverse in Facility(2004)
The Design and Implement of Mine Traverse Management System(2004)
Traverse Parameter Adjustment(2007)